The NVIDIA RTX 3080 Ti is exceptionally well-suited for running the CLIP ViT-H/14 model. The RTX 3080 Ti boasts 12GB of GDDR6X VRAM, while CLIP ViT-H/14, when operating in FP16 precision, only requires approximately 2GB. This leaves a substantial 10GB VRAM headroom, ensuring that the model and its associated processes have ample memory to operate without encountering out-of-memory errors, even with larger batch sizes or when combined with other memory-intensive tasks. The RTX 3080 Ti's memory bandwidth of 0.91 TB/s further contributes to efficient data transfer between the GPU and memory, critical for the rapid processing of large image datasets common in CLIP applications. The Ampere architecture, with its 10240 CUDA cores and 320 Tensor Cores, provides significant computational power for both inference and fine-tuning tasks.
Given the abundant VRAM headroom, users can experiment with larger batch sizes to maximize throughput. Utilizing TensorRT for optimized inference is highly recommended to further boost performance. While FP16 offers a good balance of speed and accuracy, consider experimenting with INT8 quantization to potentially increase inference speed even further, though this may come at a slight reduction in accuracy. Monitor GPU utilization during inference to ensure optimal performance; if the GPU isn't fully utilized, increasing the batch size or running multiple concurrent inference streams can improve efficiency.